Topic
Workflow
About: Workflow is a research topic. Over the lifetime, 31996 publications have been published within this topic receiving 498339 citations.
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TL;DR: The empirical study based on real-world applications from Pegasus workflow management system reveals that the NN-DNSGA-II algorithm significantly outperforms the other alternatives in most cases with respect to metrics used for DMOPs with unknown true Pareto-optimal front, including the number of non-dominated solutions, Schott’s spacing and Hypervolume indicator.
106 citations
Proceedings Article•
01 Jan 1999
106 citations
TL;DR: A stringent workflow of quality control steps during and after acquisition of T1-weighted images is proposed, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes.
Abstract: In structural magnetic resonance imaging motion artifacts are common, especially when not scanning healthy young adults. It has been shown that motion affects the analysis with automated image-processing techniques (e.g. FreeSurfer). This can bias results. Several developmental and adult studies have found reduced volume and thickness of gray matter due to motion artifacts. Thus, quality control is necessary in order to ensure an acceptable level of quality and to define exclusion criteria of images (i.e. determine participants with most severe artifacts). However, information about the quality control workflow and image exclusion procedure is largely lacking in the current literature and the existing rating systems differ. Here we propose a stringent workflow of quality control steps during and after acquisition of T1-weighted images, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes. As an underlying aim we established a thorough quality control rating system for T1-weighted images and applied it to the analysis of developmental clinical data using the automated processing pipeline FreeSurfer. This hands-on workflow and quality control rating system will aid researchers in minimizing motion artifacts in the final data set, and therefore enhance the quality of structural magnetic resonance imaging studies.
106 citations
01 Jan 2000
TL;DR: This chapter presents the formal aspects of the modeling framework of the MILANO workflow management system, which is based on a net-theoretical modeling framework which lets simple process models deliver a large class of services to its users.
Abstract: In order to support both the redesign of a Business Process and its continuous improvement, the technology supporting it must be as flexible as possible. Since workflow management systems are the main technology for supporting Business Processes, they and, in particular, their modeling framework must satisfy a long list of apparently conflicting requirements: the models must be both cognitive artifacts and executable programs; they must be simple and yet able to support exceptions; they must support both static and dynamic changes. In this chapter, after briefly discussing the above requirements, we present the formal aspects of the modeling framework of the MILANO workflow management system. Its flexibility is based on a net-theoretical modeling framework which lets simple process models deliver a large class of services to its users.
106 citations